Dynamic Resource Scaling with Azure Alert Rules

Question

Pulumi · Accepted Answer

Dynamic resource scaling with Azure can be achieved by creating alert rules that monitor the metrics of your resources and trigger actions, such as scaling out or scaling in your services based on predefined criteria.

To implement this, you would define Azure Monitor Alert Rules that monitor specific metrics (like CPU utilization or memory usage) for resources in a scale set, and take action by calling Azure Functions or Logic Apps that perform the scaling operation.

Here is a Python program that utilizes Pulumi to create an alert rule that triggers an action group when a certain metric threshold is crossed. This example assumes you have a scale set and an action group already set up to handle the scaling when the alert is triggered.

```python
import pulumi
import pulumi_azure_native as azure_native

# Replace these values with the ones from your own Azure setup
resource_group_name = "myResourceGroup"
scale_set_name = "myScaleSet"
action_group_name = "myActionGroup"

# Define the metric alert criteria
metric_alert_criteria = azure_native.insights.MetricAlertCriterionArgs(
    criterion_type="StaticThresholdCriterion",
    metric_name="Percentage CPU",
    metric_namespace="Microsoft.Compute/virtualMachineScaleSets",
    name="HighCPUUsage",
    operator="GreaterThan",
    threshold=75.0,
    time_aggregation="Average",
)

# Define the metric alert rule
metric_alert_rule = azure_native.insights.MetricAlertRuleArgs(
    resource_group_name=resource_group_name,
    window_size="PT5M",
    evaluation_frequency="PT1M",
    description="This rule scales out the scale set if the average CPU usage is over 75%",
    enabled=True,
    scopes=[f"/subscriptions/{pulumi.config.get('azure:subscriptionId')}/resourceGroups/{resource_group_name}/providers/Microsoft.Compute/virtualMachineScaleSets/{scale_set_name}"],
    criteria=[metric_alert_criteria],
    actions=[azure_native.insights.AlertRuleActionArgs(
        action_group_id=f"/subscriptions/{pulumi.config.get('azure:subscriptionId')}/resourceGroups/{resource_group_name}/providers/microsoft.insights/actionGroups/{action_group_name}"
    )]
)

# Creating a Metric Alert Rule resource using the defined args
metric_alert_resource = azure_native.insights.MetricAlertResource("highCpuUsageAlert",
    resource_group_name=resource_group_name,
    location="Global",
    alert_rule=metric_alert_rule)

# Export the resource ID of the created MetricAlertResource
pulumi.export("metricAlertResourceId", metric_alert_resource.id)
```

This Pulumi program does the following:

1. Imports the required Pulumi and Azure-native modules.
2. Sets up a few constants that you would replace with your actual resource names and identifiers in Azure.
3. Defines the metric alert criteria using the `MetricAlertCriterionArgs` class from the `azure_native.insights` module which is a static threshold for the CPU usage. In this case, it triggers when the average CPU usage is greater than 75%.
4. Creates the metric alert rule `MetricAlertRuleArgs`, specifying the frequency to evaluate the metric, the window size to aggregate, and the criteria to use for triggering.
5. Creates an alert rule resource (`MetricAlertResource`) with a name `"highCpuUsageAlert"`, which includes the action that references an action group defined in your Azure environment. This action group would contain the steps to scale out your resource (not covered in this example).
6. Exports the ID of the created metric alert resource so it can be referenced or used somewhere else if necessary.

Note that the action group (`myActionGroup`) is assumed to exist and is designed to react to this alert by scaling the targeted resource.

You'll need to replace `resource_group_name`, `scale_set_name`, and `action_group_name` with the actual names of your resources in Azure. Additionally, `pulumi.config.get('azure:subscriptionId')` fetches the Azure subscription ID from the Pulumi configuration, which you need to set up before running this program.

Before running this Pulumi program, you should have the Azure CLI and Pulumi CLI installed and configured on your machine with the necessary authorization to create resources in your Azure subscription. After running `pulumi up`, and if all precondition resources like Virtual Machine Scale Sets and Action Groups are configured correctly, this program will set up an auto-scaling mechanism via Azure Monitor Alert Rules.